摘要
将常规测井资料及其解释成果中的地质参数资料同岩芯资料相结合 ,提取反映沉积微相的特征参数 ,用 Bayes逐步判别法建立研究区域的特征参数与沉积相相互转换的数值模型 ,根据此模型对未取芯井段的沉积微相进行自动识别。提供了一种从数值模型角度进行沉积微相研究的辅助方法 。
The characteristic parameters of sedimentary microfacies are obtained by combining well logs and the analyzed results with core information. The numerical well logging microfacies model is established by means of Bayes stepwise discrimination method. Based on the method above, the non cores drills' sedimentary microfacies types are automatically discriminated. Logging data from several wells located in the Luojia Field have been processed by this numerical model. The results obtained coincide better with the microfacies of non cores drills which are identified by geologists. So this paper offers a supplementary method for sedimentary microfacies analysis from the numerical model, and it is very useful to the sedimentary microfacies of non cores drills.
出处
《成都理工学院学报》
CAS
CSCD
北大核心
2001年第3期273-278,共6页
Journal of Chengdu University of Technology
关键词
沾化凹陷
沙四段
近岸水下扇
沉积微相
Bayes逐步判别法
测井资料
油气勘探
Zhanhua depression
fourth member stratum of Shahejie Formation
nearshore subaqueous fan
sedimentary microfacies
Bayes stepwise discriminant analysis